Interdisciplinary research in artificial intelligence: challenges and opportunities
The use of artificial intelligence (AI) in a variety of research fields is speeding up multiple
digital revolutions, from shifting paradigms in healthcare, precision medicine and wearable …
digital revolutions, from shifting paradigms in healthcare, precision medicine and wearable …
The neural code for “face cells” is not face-specific
Face cells are neurons that respond more to faces than to non-face objects. They are found
in clusters in the inferotemporal cortex, thought to process faces specifically, and, hence …
in clusters in the inferotemporal cortex, thought to process faces specifically, and, hence …
[HTML][HTML] Testing methods of neural systems understanding
GW Lindsay, D Bau - Cognitive Systems Research, 2023 - Elsevier
Neuroscientists apply a range of analysis tools to recorded neural activity in order to glean
insights into how neural circuits drive behavior in organisms. Despite the fact that these tools …
insights into how neural circuits drive behavior in organisms. Despite the fact that these tools …
Face identity coding in the deep neural network and primate brain
A central challenge in face perception research is to understand how neurons encode face
identities. This challenge has not been met largely due to the lack of simultaneous access to …
identities. This challenge has not been met largely due to the lack of simultaneous access to …
[HTML][HTML] Deep Face Decoder: towards understanding the embedding space of convolutional networks through visual reconstruction of deep face templates
Advances in deep learning and convolutional neural networks (ConvNets) have driven
remarkable face recognition (FR) progress recently. However, the black-box nature of …
remarkable face recognition (FR) progress recently. However, the black-box nature of …
Modeling biological face recognition with deep convolutional neural networks
LE van Dyck, WR Gruber - Journal of Cognitive Neuroscience, 2023 - ieeexplore.ieee.org
Deep convolutional neural networks (DCNNs) have become the state-of-the-art
computational models of biological object recognition. Their remarkable success has helped …
computational models of biological object recognition. Their remarkable success has helped …
Use of artificial intelligence in activating the role of Saudi universities in joint scientific research between university teachers and students
A Albasalah, S Alshawwa, R Alarnous - Plos one, 2022 - journals.plos.org
Scientific research in Saudi Arabia's universities has undergone significant changes in
recent years with the speed of higher education expansion and the opening of new …
recent years with the speed of higher education expansion and the opening of new …
Twin identification over viewpoint change: A deep convolutional neural network surpasses humans
Deep convolutional neural networks (DCNNs) have achieved human-level accuracy in face
identification (Phillips et al., 2018), though it is unclear how accurately they discriminate …
identification (Phillips et al., 2018), though it is unclear how accurately they discriminate …
Seeing through disguise: Getting to know you with a deep convolutional neural network
People use disguise to look unlike themselves (evasion) or to look like someone else
(impersonation). Evasion disguise challenges human ability to see an identity across …
(impersonation). Evasion disguise challenges human ability to see an identity across …
Facial expression is retained in deep networks trained for face identification
Facial expressions distort visual cues for identification in two-dimensional images. Face
processing systems in the brain must decouple image-based information from multiple …
processing systems in the brain must decouple image-based information from multiple …